FIG. 1 shows schematically the architecture of a cellular telephone network. The network comprises a number of base stations 1, each of which is capable of bidirectional radio communication with mobile stations 2 that are within its range. Each base station is connected to a core network function 3, which controls the handling and routing of calls to and from the mobile stations 2, and between terminals in the network and terminals in other networks 4, to which it is connected.
The range of operation of a base station forms a cell 5. The geographical size of the cell is dependent on a number of factors. The cell cannot extend beyond the range within which the base station can successfully communicate with the mobile station. This is dependent on the landscape of the region around the base station, and thus the objects there that may disrupt radio signals, on the sensitivity of reception of the mobile stations and the base station and on the maximum transmit and receive power available to the mobile stations and the base station.
Some cellular telephone networks can use macrodiversity. In macrodiversity a mobile station can communicate traffic data with two or more base stations simultaneously (“soft hand-off”). This can provide a number of advantages, including reducing the risk of signal degradation due to interference and facilitating the hand over of the mobile station from one cell to another.
Radio network planning is a complicated process that mainly consists of network dimensioning, detailed capacity and coverage planning, and network optimisation.
When a cellular telephone network is to be deployed the network planners must decide on the locations where the base stations are to be installed, and the configuration of those base stations. In doing so they will wish to minimise the number of base stations that are required, so as to keep costs low, whilst ensuring that the network can provide a desired level of service. These decisions are complex. For example, as the cell size is increased the number of base stations that are required is reduced, but the battery life of the mobile stations will shorten (since they will need to use greater transmit power) and the level of interference will increase, especially in CDMA (code division multiple access) systems where more than one nearby base station or mobile station may transmit on the same frequency simultaneously. One example of such as system is the 3G (third generation)/WCDMA (wideband CDMA) system which is currently being implemented. The complexity increases in systems that implement macrodiversity since the power required is also dependent on the incidence of soft hand-off. In spite of these difficulties, the cost of network equipment makes it is highly desirable to optimise the planning as much as possible.
The planning decision is based on an assessment of the power required by each base station. This is dependent on a number of factors, notably:                1. the requirements of any standards with which the network must comply;        2. attenuation and other forms of signal degradation due to the landscape around the base station; and        3. for base stations operating in systems that allow macrodiversity, the degree to which the operations of nearby base stations are likely to affect the required power.        
Factor 1is well-defined. However, factors 2 and 3 are extremely difficult to determine in practice. With sufficiently detailed modelling it might be possible to make an accurate estimate of factors 2 and 3 on a small scale using prior art techniques, but in practice such modelling would require far too much calculation and measurement to be useful for planning a network. Therefore, network planning must be based on an approximation of the effects of factors 2 and 3. That estimate is often taken as being common to all base stations in a system, or to all base stations in a certain environment (e.g. urban or suburban). Yet factors such as MDC gain and fast-fading margin differ in practice from cell to cell. As a result each sector/cell may not be optimally planned with a proper set of parameters, which in return degrades the capacity/coverage in the network.
In practice, network planning is conventionally performed by choosing network parameter values that are either statistically obtained from measurements or verified by link-level simulations. For example, it is common to use MDC (macrodiversity combining) gain and fast-fading margin derived from link-level simulations for the link budget calculation in CDMA networks (see Jaana Laiho, Achim Wacker, Tomas Novosad, “Radio Network Planning and Optimisation for UMTS”, John Wiley & Sons, Ltd.). The values of MDC gain and fast-fading margin used in network planning are typically taken to be the same for each cell/sector. In other words, those parameter values are not site-specific or location-dependent.
WO 02/35872 discloses a method for planning a CDMA network. Domains of base stations are calculated using geographical information. Then the service areas of the base stations are determined, taking macrodiversity into account on a block-by-block (pixel-by-pixel) basis. Neither macrodiversity gain nor fading margin is calculated, or identified as a tool for network planning.
U.S. Pat. No. 6,389,294 discloses a method of determining the effect of radio wave multipath fading in different sub-areas of a desired area in a radio system.
U.S. Pat. No. 6,477,376 discloses a method of optimising the designing of cell sites for mobile communications systems using uplink parameters. The method selects a propagation model to be used in calculating the predicted signal loss.
As outlined above, any improvement in the accuracy of the data that is available for network planning, and that can be obtained with a reasonable level of computation, would be highly valuable. It could increase the utilisation of radio resources in the network, and reduce the need for adjustments to optimise the network after deployment.